Senior Artificial Intelligence Engineer

Grey Chain; United States; Remote; USD 140,000 - 210,000; Full time

Job summary

Grey Chain is seeking an experienced AI Engineer to design, build, and operate enterprise AI and Generative AI capabilities. The role supports the AI CoE, Agentic AI Ecosystem, Enterprise AI Platform, and Trade Virtual Assistant, delivering secure, observable AI services aligned with strategy and standards.

Candidates should have 7+ years of software/AI engineering and hands-on Azure AI experience, including OpenAI, Foundry, and Fabric. Strong Python, API, CI/CD, and MLOps skills are essential.

Qualifications

• 7+ years in software, data, ML, or AI engineering with enterprise delivery.
• Hands-on GenAI, LLMs, prompt engineering, RAG, AI agents, multi-agent systems.
• Azure AI stack experience including OpenAI, Foundry, Search, Functions, AKS, API Management.
• Experience with Python, APIs, containers, CI/CD, MLOps, observability, testing, enterprise integration.
• Banking or financial-services exposure is a plus.

Responsibilities

• Develop Python-based AI services, prompt workflows, RAG pipelines, embeddings, retrieval.
• Configure Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Functions, AKS, API Management, Fabric.
• Implement APIs, tool integrations, function calling, data connectors, tests, CI/CD, MLOps pipelines.
• Monitor quality, latency, reliability, safety, cost; support controlled production releases.
• Produce maintainable code, docs, deployment instructions, and runbooks.

Skills

Python

LLM application development

Prompt engineering

RAG

AI agents

Multi-agent systems

MCP

Tool calling

Function calling

Automated evaluation

Education

Bachelor's degree in CS/AI/DS/IT/Engineering

Masters degree preferred

Tools

Azure OpenAI

Azure AI Foundry

Azure AI Search

Azure Functions

AKS

Azure API Management

Microsoft Fabric

Git & CI/CD

Job description

Role Title

AI Engineer

Department

Artificial Intelligence / Technology

Years of Experience

7+ years

Role Purpose

Design, build, test, and operate enterprise AI and Generative AI capabilities supporting clients AI CoE, Agentic AI Ecosystem, Enterprise AI Platform, and Trade Virtual Assistant. The role delivers secure, reusable, and observable AI services aligned with clients AI Strategy, engineering standards, and digital transformation priorities.

Key Responsibilities

Strategic Responsibilities

• Contribute to reusable AI engineering patterns, platform accelerators, and technical standards.
• Assess suitable LLM, RAG, agent, MCP, tool-calling, and function-calling approaches against business and non-functional needs.

Delivery Responsibilities

• Develop Python-based AI services, prompt workflows, RAG pipelines, embeddings, retrieval, AI agents, and multi-agent components.
• Configure and integrate Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Functions, AKS, Azure API Management, and Microsoft Fabric.
• Implement APIs, tool integrations, function calling, data connectors, automated tests, evaluation datasets, CI/CD, and MLOps pipelines.
• Monitor quality, latency, reliability, safety, and cost; investigate defects and support controlled production releases.
• Produce maintainable code, technical documentation, deployment instructions, and operational runbooks.

Governance Responsibilities

• Apply Responsible AI, security, privacy, compliance, access-control, content-safety, and data-handling requirements.
• Maintain traceability for prompts, models, retrieval sources, evaluations, changes, and releases.
• Support architecture, security, risk, and governance reviews and remediate identified control gaps.

Stakeholder Management Responsibilities

• Work with the Senior AI Engineer, AI Architect, product owners, business analysts, data teams, platform teams, and vendors.
• Explain engineering progress, dependencies, risks, and technical choices clearly to delivery stakeholders.

Required Experience

• 7+ years in software, data, ML, or AI engineering with hands‑on enterprise delivery.
• Practical experience with GenAI, LLMs, prompt engineering, RAG, AI agents, multi-agent systems, MCP, tool calling, and function calling.
• Hands‑on Azure AI experience including Azure OpenAI, Azure AI Foundry, Azure AI Search, Azure Functions, AKS, Azure API Management, and Microsoft Fabric.
• Experience with Python, APIs, containers, CI/CD, MLOps, observability, testing, and enterprise integration.
• Banking or financial‑services exposure preferred, including retail, corporate, trade finance, digital banking, risk, or compliance.

Required Skills

Technical Skills

Python; LLM application development; Prompt engineering; RAG; AI agents; Multi-agent systems; MCP; Tool calling; Function calling; Automated evaluation

Platform Skills

Azure OpenAI; Azure AI Foundry; Azure AI Search; Azure Functions; AKS; Azure API Management; Microsoft Fabric; Git and CI/CD

Integration Skills

REST APIs; Data connectors; Event integration; Authentication and authorization; Enterprise application integration

Governance & Security Skills

Responsible AI; AI governance; Security and compliance; MLOps; Observability; Model and prompt monitoring; Enterprise standards

Leadership / Business Skills

Problem solving; Agile delivery; Documentation; Collaboration; Clear stakeholder communication

Preferred Tools and Certifications

Requirement

Microsoft Certified: Azure AI Engineer Associate

Build and deploy AI solutions on Microsoft Azure.

Preferred

Microsoft Certified: Azure Fundamentals

Demonstrate foundational Azure cloud knowledge.

Preferred

Generative AI Certification

Apply LLM, prompt, RAG, and responsible GenAI practices.

Preferred

Python Certification

Demonstrate applied Python programming capability.

Education

Bachelors degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, Engineering, or a related discipline is mandatory. A Masters degree is preferred.